--------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/log_main.log
  log type:  text
 opened on:  10 Feb 2024, 12:03:24

. 
. 
. 
. ****** build dataset 
. qui do "$pathcode/0.build_dataset_F.do"

. 
. 
. *----- 
. *-------------------------------
. *---  Figure 1 -- This is a screenshot of QVSR tool, no code needed
. 
. 
. 
. *----- 
. *-------------------------------
. *---  Figure 2 -- 
. 
. *** note that for presentational purposes, for Likert+, 2 observations from one very parsely populated response ca
> tegorie (= 5, 2 obs total) are dropped to compute the figure. These 2 individuals both donated 100 dollars, which 
> messes up the Y-axis.
. 
. cd "$pathtemp"
/Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp

. 
. gen temp_LPP3 = votes_gunw1LPP3N
(13 missing values generated)

. replace temp_LPP3 = . if votes_gunw1LPP3 == 5 & method == 2
(2 real changes made, 2 to missing)

. gen temp_don_C_gun  = don_C_gun 
(264 missing values generated)

. replace temp_don_C_gun = . if votes_gunw1LPP3 == 5 & method == 2
(2 real changes made, 2 to missing)

. 
. 
. egen mean_gunL = mean(don_C_gun) if method == 1 , by(votes_gunw1LPP3N)
(2,608 missing values generated)

. egen mean_gunLp = mean(temp_don_C_gun) if method == 2 , by(temp_LPP3)
(2,614 missing values generated)

. egen mean_gunQV = mean(don_C_gun) if method == 3 , by(votes_gunw1LPP3N)
(2,706 missing values generated)

. 
. egen count_gun = count(votes_gunw1N), by(method votes_gunw1LPP3N)

. egen count_gunLPP3 = count(votes_gunw1N) if method == 2, by(temp_LPP3)
(2,614 missing values generated)

. 
. 
. tw (lfitci don_C_gun votes_gunw1LPP3N if method == 1,  level(95) clp(shortdash) clc(black) yline(-20) yline(20)) /
> //
> (scatter mean_gunL votes_gunw1LPP3N if method == 1 [w=count_gun],  mc(black)  msymbol(oh) ///
> ylabel(-40(20)40 , angle(horizontal)labsize(medsmall)) yline(0) xlabel(0(0.1)1, angle(horizontal)labsize(medsmall)
> ) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("Likert")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "gun_fig2L.gph", replace 
(file gun_fig2L.gph not found)
file gun_fig2L.gph saved

. 
. 
. tw (lfitci temp_don_C_gun temp_LPP3 if method == 2,  level(95) clp(dash_dot) clc(black) yline(-20) yline(20)) ///
> (scatter mean_gunLp temp_LPP3 if method == 2 [w=count_gunLPP3],  mc(black)  msymbol(oh) ///
> ylabel(-40(20)40 , angle(horizontal)labsize(medsmall)) yline(0) xlabel(0(0.1)1, angle(horizontal)labsize(medsmall)
> ) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("Likert +, ")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "gun_fig2Lpp3.gph", replace 
(file gun_fig2Lpp3.gph not found)
file gun_fig2Lpp3.gph saved

. 
. 
. tw (lfitci don_C_gun votes_gunw1LPP3N if method == 3,  level(95) clp(shortdash) clc(black) yline(-20) yline(20)) /
> //
> (scatter mean_gunQV votes_gunw1LPP3N if method == 3 [w=count_gun],  mc(black)  msymbol(oh) ///
> ylabel(-40(20)40 , angle(horizontal)labsize(medsmall)) yline(0) xlabel(0(0.1)1, angle(horizontal)labsize(medsmall)
> ) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("QVSR")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "gun_fig2QV.gph", replace 
(file gun_fig2QV.gph not found)
file gun_fig2QV.gph saved

. 
. 
. **** figures below 
. 
. 
. gr tw (hist votes_gunw1LPP3N if  method == 1, frac ///
> discrete bfcolor(teal)  blcolor(white) title("")) ,  leg(off)  ///
> graphr(fc(white) lc(white) ifc(white) ilc(white)) title("", size(medium)) yti("") xti("") ///
> ysc(range(0 .5)) ylab(0(.1).5)  ///
> xsc(range(0 1)) xlab(0(0.1)1) fysize(20) 

. graph save "gunLw1N.gph", replace 
(file gunLw1N.gph not found)
file gunLw1N.gph saved

.         
. gr tw (hist votes_gunw1LPP3N if  method == 2, frac ///
> discrete bfcolor(teal)  blcolor(white) title("")) ,  leg(off)  ///
> graphr(fc(white) lc(white) ifc(white) ilc(white)) title("", size(medium)) yti("") xti("") ///
> ysc(range(0 .5)) ylab(0(.1).5)  ///
> xsc(range(0 1)) xlab(0(0.1)1) fysize(20) 

. graph save "gunLpp3w1N.gph", replace 
(file gunLpp3w1N.gph not found)
file gunLpp3w1N.gph saved

. 
. gr tw (hist votes_gunw1LPP3N if  method == 3, frac ///
> discrete bfcolor(teal)  blcolor(white) title("")) ,  leg(off)  ///
> graphr(fc(white) lc(white) ifc(white) ilc(white)) title("", size(medium)) yti("") xti("") ///
> ysc(range(0 .5)) ylab(0(.1).5)  ///
> xsc(range(0 1)) xlab(0(0.1)1) fysize(20) 

. graph save "gunQVw1N.gph", replace 
(file gunQVw1N.gph not found)
file gunQVw1N.gph saved

. 
. 
. graph combine  "gun_fig2Lpp3.gph"  "gun_fig2L.gph" "gun_fig2QV.gph"  ///
>  "gunLpp3w1N.gph" "gunLw1N.gph" "gunQVw1N.gph" , ///
> col(3) title("", size(zero)) 

. cd "$pathfig"
/Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/fig

. graph export "Fig2.pdf", replace
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/fig/Fig2.pdf saved as PDF
    format

. 
. erase "$pathtemp/gun_fig2L.gph"

. erase "$pathtemp/gun_fig2Lpp3.gph"

. erase "$pathtemp/gun_fig2QV.gph"

. erase "$pathtemp/gunLpp3w1N.gph"

. erase "$pathtemp/gunLw1N.gph"

. erase "$pathtemp/gunQVw1N.gph"

. 
. 
. *----- 
. *-------------------------------
. *---  Figure 3 -- 
. 
. cd "$pathtemp"
/Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp

. 
. matrix EV_fig3 = J(6,6,0)

. matrix colnames EV_fig3 = "Likert" " " "Likert +" " " "QVSR" " " 

. matrix rownames EV_fig3 = "Gun-related Donations" ///
> "Immigration-related Donations" ///
> "Minimum Wage-related Writing" /// 
> "Abortion-related Writing" ///
> "Punish abs" ///
> "Punish proportion"

. 
. 
. regress don_C_gunST c.votes_gunw1LPP3N##i.method i.block

      Source |       SS           df       MS      Number of obs   =     3,670
-------------+----------------------------------   F(45, 3624)     =     22.38
       Model |  798.525398        45  17.7450088   Prob > F        =    0.0000
    Residual |  2872.94166     3,624   .79275432   R-squared       =    0.2175
-------------+----------------------------------   Adj R-squared   =    0.2078
       Total |  3671.46705     3,669  1.00067241   Root MSE        =    .89037

-------------------------------------------------------------------------------------------
              don_C_gunST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
         votes_gunw1LPP3N |   .9155763   .0727683    12.58   0.000     .7729054    1.058247
                          |
                   method |
                 Likert+  |  -.0586373   .0777224    -0.75   0.451    -.2110214    .0937467
                    QVSR  |  -.2396741   .0938318    -2.55   0.011    -.4236425   -.0557056
                          |
method#c.votes_gunw1LPP3N |
                 Likert+  |    .185417    .102993     1.80   0.072    -.0165131    .3873471
                    QVSR  |   .5842363   .1402445     4.17   0.000     .3092703    .8592024
                          |
                    block |
                    1120  |  -.2487885    .250691    -0.99   0.321     -.740298    .2427209
                    1130  |  -.3966028   .2549053    -1.56   0.120    -.8963751    .1031694
                    1210  |  -.2927699   .2067436    -1.42   0.157    -.6981152    .1125754
                    1221  |   -.413507   .2225652    -1.86   0.063    -.8498726    .0228586
                    1222  |   -.266392   .2122754    -1.25   0.210    -.6825832    .1497992
                    1223  |  -.2843109   .2052026    -1.39   0.166    -.6866349    .1180132
                    1231  |  -.5636415   .3174459    -1.78   0.076    -1.186032     .058749
                    1232  |   -.177901   .2377542    -0.75   0.454    -.6440462    .2882443
                    1233  |  -.3604687    .210161    -1.72   0.086    -.7725144     .051577
                    1311  |  -.4085868    .246968    -1.65   0.098    -.8927969    .0756234
                    1312  |  -.3226036   .2250986    -1.43   0.152    -.7639362    .1187291
                    1313  |  -.4797113   .2152738    -2.23   0.026     -.901781   -.0576415
                    1321  |  -.4226038    .190761    -2.22   0.027    -.7966135   -.0485942
                    1322  |  -.3706053   .1964165    -1.89   0.059    -.7557032    .0144925
                    1323  |   -.468324   .1960948    -2.39   0.017     -.852791   -.0838569
                    1331  |    -.42291   .2275173    -1.86   0.063    -.8689847    .0231647
                    1332  |  -.3655984   .2266153    -1.61   0.107    -.8099046    .0787077
                    1333  |  -.3856322   .2165425    -1.78   0.075    -.8101894     .038925
                    2010  |  -.3518421   .2722425    -1.29   0.196    -.8856059    .1819216
                    2020  |  -.2324373   .3846156    -0.60   0.546    -.9865219    .5216473
                    2030  |  -.1904329   .2352666    -0.81   0.418    -.6517011    .2708353
                    3115  |   .0548008   .1977886     0.28   0.782    -.3329873    .4425889
                    3116  |  -.0562471   .1987009    -0.28   0.777    -.4458238    .3333296
                    3117  |   .0325985   .1898481     0.17   0.864    -.3396212    .4048182
                    3120  |  -.3004722    .257411    -1.17   0.243    -.8051571    .2042127
                    3135  |  -.4259117   .2266637    -1.88   0.060    -.8703129    .0184895
                    3136  |  -.2722979   .2434767    -1.12   0.263    -.7496629    .2050672
                    3137  |  -.0909896   .2251801    -0.40   0.686     -.532482    .3505028
                    3215  |  -.0713798   .1988715    -0.36   0.720    -.4612911    .3185315
                    3216  |  -.0428566   .2017429    -0.21   0.832    -.4383974    .3526843
                    3217  |  -.0788716   .1993408    -0.40   0.692     -.469703    .3119597
                    3220  |  -.2084613   .2243673    -0.93   0.353    -.6483601    .2314374
                    3235  |  -.4112227   .2040383    -2.02   0.044     -.811264   -.0111815
                    3236  |  -.3645233   .2258646    -1.61   0.107    -.8073576    .0783111
                    3237  |  -.4279121   .2550183    -1.68   0.093    -.9279057    .0720815
                    3315  |   -.008438   .2341514    -0.04   0.971    -.4675195    .4506436
                    3316  |  -.1545187   .2575824    -0.60   0.549    -.6595395    .3505022
                    3317  |  -.2565085    .239322    -1.07   0.284    -.7257276    .2127107
                    3320  |  -.8715335    .262947    -3.31   0.001    -1.387072   -.3559946
                    3330  |  -.3128962   .2237111    -1.40   0.162    -.7515084    .1257159
                          |
                    _cons |  -.4159692   .1933267    -2.15   0.031    -.7950093   -.0369292
-------------------------------------------------------------------------------------------

. lincom c.votes_gunw1LPP3N + 1.method#c.votes_gunw1LPP3N 

 ( 1)  votes_gunw1LPP3N + 1b.method#co.votes_gunw1LPP3N = 0

------------------------------------------------------------------------------
 don_C_gunST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .9155763   .0727683    12.58   0.000     .7729054    1.058247
------------------------------------------------------------------------------

. matrix EV_fig3[1,1] = r(estimate)

. matrix EV_fig3[1,2] = r(se)

. lincom c.votes_gunw1LPP3N + 2.method#c.votes_gunw1LPP3N 

 ( 1)  votes_gunw1LPP3N + 2.method#c.votes_gunw1LPP3N = 0

------------------------------------------------------------------------------
 don_C_gunST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   1.100993   .0830066    13.26   0.000      .938249    1.263738
------------------------------------------------------------------------------

. matrix EV_fig3[1,3] = r(estimate)

. matrix EV_fig3[1,4] = r(se)

. lincom c.votes_gunw1LPP3N + 3.method#c.votes_gunw1LPP3N 

 ( 1)  votes_gunw1LPP3N + 3.method#c.votes_gunw1LPP3N = 0

------------------------------------------------------------------------------
 don_C_gunST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   1.499813   .1288103    11.64   0.000     1.247265    1.752361
------------------------------------------------------------------------------

. matrix EV_fig3[1,5] = r(estimate)

. matrix EV_fig3[1,6] = r(se)

. 
. 
. regress don_C_wall_inST c.votes_wall_inw1LPP3N##i.method  i.block

      Source |       SS           df       MS      Number of obs   =     3,670
-------------+----------------------------------   F(45, 3624)     =     14.13
       Model |  547.473851        45  12.1660856   Prob > F        =    0.0000
    Residual |  3120.01838     3,624  .860932223   R-squared       =    0.1493
-------------+----------------------------------   Adj R-squared   =    0.1387
       Total |  3667.49223     3,669  .999589051   Root MSE        =    .92786

-----------------------------------------------------------------------------------------------
              don_C_wall_inST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
------------------------------+----------------------------------------------------------------
         votes_wall_inw1LPP3N |   .5114665   .0751858     6.80   0.000     .3640559    .6588772
                              |
                       method |
                     Likert+  |   -.091872   .0662627    -1.39   0.166    -.2217878    .0380439
                        QVSR  |  -.1924184   .0802178    -2.40   0.017     -.349695   -.0351418
                              |
method#c.votes_wall_inw1LPP3N |
                     Likert+  |     .17196   .1001846     1.72   0.086    -.0244638    .3683838
                        QVSR  |   .3322835   .1322229     2.51   0.012     .0730447    .5915223
                              |
                        block |
                        1120  |  -.3114163   .2622465    -1.19   0.235    -.8255817    .2027491
                        1130  |   .0335254   .2660153     0.13   0.900    -.4880293    .5550801
                        1210  |  -.0207852   .2154553    -0.10   0.923    -.4432109    .4016404
                        1221  |  -.2399344     .23294    -1.03   0.303    -.6966409    .2167721
                        1222  |  -.1680903   .2223797    -0.76   0.450    -.6040921    .2679114
                        1223  |  -.2236336   .2145687    -1.04   0.297     -.644321    .1970539
                        1231  |  -.0612314   .3308735    -0.19   0.853    -.7099481    .5874854
                        1232  |  -.1174615   .2479451    -0.47   0.636    -.6035872    .3686643
                        1233  |  -.0957169   .2193365    -0.44   0.663    -.5257521    .3343184
                        1311  |  -.1441998   .2574376    -0.56   0.575    -.6489369    .3605373
                        1312  |   .0181217     .23457     0.08   0.938    -.4417807    .4780242
                        1313  |  -.1166864   .2243822    -0.52   0.603    -.5566144    .3232415
                        1321  |  -.3316601   .2005127    -1.65   0.098    -.7247891    .0614689
                        1322  |  -.1527018   .2057939    -0.74   0.458    -.5561852    .2507817
                        1323  |  -.4541214   .2058265    -2.21   0.027    -.8576687   -.0505741
                        1331  |  -.0456267   .2376468    -0.19   0.848    -.5115616    .4203081
                        1332  |  -.1863416   .2373464    -0.79   0.432    -.6516874    .2790042
                        1333  |  -.0790731   .2261409    -0.35   0.727    -.5224492     .364303
                        2010  |   .0336627   .2837531     0.12   0.906     -.522669    .5899943
                        2020  |  -.4021774   .4019605    -1.00   0.317    -1.190269    .3859139
                        2030  |  -.1175347   .2451509    -0.48   0.632    -.5981822    .3631127
                        3115  |   .2763631   .2063881     1.34   0.181    -.1282853    .6810115
                        3116  |   .1140679   .2071863     0.55   0.582    -.2921455    .5202814
                        3117  |   .1797462   .1980294     0.91   0.364     -.208514    .5680064
                        3120  |  -.2499802   .2686172    -0.93   0.352    -.7766361    .2766758
                        3135  |   .1167665   .2363518     0.49   0.621    -.3466294    .5801623
                        3136  |  -.1113393   .2537074    -0.44   0.661    -.6087627    .3860841
                        3137  |  -.0445025   .2347597    -0.19   0.850    -.5047768    .4157719
                        3215  |   .1671912   .2073432     0.81   0.420    -.2393298    .5737121
                        3216  |  -.0071516   .2102116    -0.03   0.973    -.4192964    .4049933
                        3217  |    .018074   .2077545     0.09   0.931    -.3892533    .4254013
                        3220  |  -.1778073   .2348607    -0.76   0.449    -.6382797     .282665
                        3235  |  -.0226617   .2126096    -0.11   0.915    -.4395081    .3941848
                        3236  |  -.1344732   .2353613    -0.57   0.568    -.5959271    .3269807
                        3237  |   .1478767   .2656674     0.56   0.578    -.3729957    .6687492
                        3315  |   .0782911   .2439652     0.32   0.748    -.4000317    .5566138
                        3316  |  -.0787637    .268192    -0.29   0.769     -.604586    .4470586
                        3317  |  -.2044169   .2491745    -0.82   0.412    -.6929531    .2841193
                        3320  |  -.1540349   .2745375    -0.56   0.575    -.6922984    .3842286
                        3330  |  -.1035982   .2331457    -0.44   0.657     -.560708    .3535117
                              |
                        _cons |  -.2114292   .2002464    -1.06   0.291     -.604036    .1811776
-----------------------------------------------------------------------------------------------

. lincom c.votes_wall_inw1LPP3N + 1.method#c.votes_wall_inw1LPP3N 

 ( 1)  votes_wall_inw1LPP3N + 1b.method#co.votes_wall_inw1LPP3N = 0

------------------------------------------------------------------------------
don_C_wall~T | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .5114665   .0751858     6.80   0.000     .3640559    .6588772
------------------------------------------------------------------------------

. matrix EV_fig3[2,1] = r(estimate)

. matrix EV_fig3[2,2] = r(se)

. lincom c.votes_wall_inw1LPP3N + 2.method#c.votes_wall_inw1LPP3N 

 ( 1)  votes_wall_inw1LPP3N + 2.method#c.votes_wall_inw1LPP3N = 0

------------------------------------------------------------------------------
don_C_wall~T | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .6834265   .0935708     7.30   0.000     .4999699    .8668832
------------------------------------------------------------------------------

. matrix EV_fig3[2,3] = r(estimate)

. matrix EV_fig3[2,4] = r(se)

. lincom c.votes_wall_inw1LPP3N + 3.method#c.votes_wall_inw1LPP3N 

 ( 1)  votes_wall_inw1LPP3N + 3.method#c.votes_wall_inw1LPP3N = 0

------------------------------------------------------------------------------
don_C_wall~T | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |     .84375   .1320611     6.39   0.000     .5848284    1.102672
------------------------------------------------------------------------------

. matrix EV_fig3[2,5] = r(estimate)

. matrix EV_fig3[2,6] = r(se)

. 
. 
. regress writing_minWNST c.abs_votes_minWw1LPP3N##i.method  i.block

      Source |       SS           df       MS      Number of obs   =     1,570
-------------+----------------------------------   F(45, 1524)     =      1.62
       Model |   71.740797        45  1.59423993   Prob > F        =    0.0062
    Residual |  1500.62935     1,524   .98466493   R-squared       =    0.0456
-------------+----------------------------------   Adj R-squared   =    0.0174
       Total |  1572.37015     1,569  1.00214796   Root MSE        =     .9923

------------------------------------------------------------------------------------------------
               writing_minWNST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------------------------+----------------------------------------------------------------
         abs_votes_minWw1LPP3N |   .2610863   .1231541     2.12   0.034     .0195169    .5026556
                               |
                        method |
                      Likert+  |   .0290386   .1232543     0.24   0.814    -.2127273    .2708046
                         QVSR  |   .0262838   .1284706     0.20   0.838     -.225714    .2782816
                               |
method#c.abs_votes_minWw1LPP3N |
                      Likert+  |   .0944501    .175639     0.54   0.591    -.2500697    .4389699
                         QVSR  |   .2623062   .2678557     0.98   0.328    -.2630987    .7877111
                               |
                         block |
                         1120  |  -.4048902   .4095198    -0.99   0.323    -1.208172    .3983917
                         1130  |  -.1594502   .5014405    -0.32   0.751    -1.143037    .8241363
                         1210  |   .1685575   .3655795     0.46   0.645    -.5485347    .8856498
                         1221  |  -.0089019   .3956693    -0.02   0.982    -.7850158     .767212
                         1222  |  -.0966532   .3672679    -0.26   0.792    -.8170572    .6237508
                         1223  |   .1852978   .3624893     0.51   0.609    -.5257329    .8963284
                         1231  |  -.3292503   .5230143    -0.63   0.529    -1.355154    .6966536
                         1232  |  -.1993776    .431108    -0.46   0.644    -1.045005    .6462501
                         1233  |  -.2305782   .3723307    -0.62   0.536     -.960913    .4997566
                         1311  |   .5405534   .4465583     1.21   0.226    -.3353804    1.416487
                         1312  |   -.067797   .3986006    -0.17   0.865    -.8496607    .7140668
                         1313  |   -.026458   .3682313    -0.07   0.943    -.7487517    .6958356
                         1321  |  -.2679439   .3380089    -0.79   0.428    -.9309557     .395068
                         1322  |   .2101904   .3476718     0.60   0.546    -.4717754    .8921561
                         1323  |    .137674   .3454427     0.40   0.690    -.5399195    .8152674
                         1331  |  -.1040781   .3927867    -0.26   0.791    -.8745379    .6663816
                         1332  |  -.1420784   .3930227    -0.36   0.718    -.9130011    .6288442
                         1333  |  -.1936944   .3882358    -0.50   0.618    -.9552275    .5678386
                         2010  |  -.4292035   .4822861    -0.89   0.374    -1.375218    .5168111
                         2020  |   .8200104   .5537823     1.48   0.139    -.2662455    1.906266
                         2030  |  -.1881027   .4241921    -0.44   0.658    -1.020165    .6439593
                         3115  |   .0289815    .350183     0.08   0.934    -.6579101    .7158731
                         3116  |  -.0733566   .3470056    -0.21   0.833    -.7540156    .6073024
                         3117  |  -.0900881   .3376189    -0.27   0.790    -.7523349    .5721587
                         3120  |   .5716658   .4565139     1.25   0.211    -.3237961    1.467128
                         3135  |  -.0956244    .414223    -0.23   0.817    -.9081319    .7168831
                         3136  |  -.2817494   .4307373    -0.65   0.513     -1.12665    .5631513
                         3137  |   .1123911   .3909792     0.29   0.774    -.6545232    .8793053
                         3215  |  -.0851129   .3515884    -0.24   0.809    -.7747611    .6045353
                         3216  |  -.2420057   .3601767    -0.67   0.502       -.9485    .4644887
                         3217  |  -.1559525   .3553141    -0.44   0.661     -.852909    .5410039
                         3220  |  -.0655125   .3983929    -0.16   0.869    -.8469688    .7159438
                         3235  |  -.1979406    .363814    -0.54   0.586    -.9115697    .5156884
                         3236  |   -.299822   .4055773    -0.74   0.460    -1.095371    .4957267
                         3237  |  -.2182249   .4680568    -0.47   0.641    -1.136328    .6998787
                         3315  |   .2663103   .4092044     0.65   0.515    -.5363531    1.068974
                         3316  |   .1642501   .4462789     0.37   0.713    -.7111357    1.039636
                         3317  |  -.0429583     .43072    -0.10   0.921    -.8878249    .8019084
                         3320  |  -.1019494   .4559988    -0.22   0.823    -.9964009    .7925021
                         3330  |   .4162338    .424489     0.98   0.327    -.4164106    1.248878
                               |
                         _cons |  -.1327779   .3450605    -0.38   0.700    -.8096216    .5440658
------------------------------------------------------------------------------------------------

. lincom c.abs_votes_minWw1LPP3N + 1.method#c.abs_votes_minWw1LPP3N 

 ( 1)  abs_votes_minWw1LPP3N + 1b.method#co.abs_votes_minWw1LPP3N = 0

------------------------------------------------------------------------------
writing~WNST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .2610863   .1231541     2.12   0.034     .0195169    .5026556
------------------------------------------------------------------------------

. matrix EV_fig3[3,1] = r(estimate)

. matrix EV_fig3[3,2] = r(se)

. lincom c.abs_votes_minWw1LPP3N + 2.method#c.abs_votes_minWw1LPP3N 

 ( 1)  abs_votes_minWw1LPP3N + 2.method#c.abs_votes_minWw1LPP3N = 0

------------------------------------------------------------------------------
writing~WNST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .3555364   .1272275     2.79   0.005     .1059769     .605096
------------------------------------------------------------------------------

. matrix EV_fig3[3,3] = r(estimate)

. matrix EV_fig3[3,4] = r(se)

. lincom c.abs_votes_minWw1LPP3N + 3.method#c.abs_votes_minWw1LPP3N 

 ( 1)  abs_votes_minWw1LPP3N + 3.method#c.abs_votes_minWw1LPP3N = 0

------------------------------------------------------------------------------
writing~WNST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .5233925   .2385803     2.19   0.028      .055412     .991373
------------------------------------------------------------------------------

. matrix EV_fig3[3,5] = r(estimate)

. matrix EV_fig3[3,6] = r(se)

. 
. 
. regress writing_abortionNST c.abs_votes_abortion_inw1LPP3N##i.method  i.block, 

      Source |       SS           df       MS      Number of obs   =     1,569
-------------+----------------------------------   F(45, 1523)     =      3.31
       Model |   140.19987        45  3.11555266   Prob > F        =    0.0000
    Residual |  1431.73637     1,523  .940076405   R-squared       =    0.0892
-------------+----------------------------------   Adj R-squared   =    0.0623
       Total |  1571.93623     1,568  1.00251035   Root MSE        =    .96958

-------------------------------------------------------------------------------------------------------
                  writing_abortionNST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------------------+----------------------------------------------------------------
         abs_votes_abortion_inw1LPP3N |   .3837219   .1162126     3.30   0.001     .1557683    .6116756
                                      |
                               method |
                             Likert+  |  -.1266345   .1258656    -1.01   0.315    -.3735228    .1202537
                                QVSR  |  -.2570649   .1309017    -1.96   0.050    -.5138316   -.0002982
                                      |
method#c.abs_votes_abortion_inw1LPP3N |
                             Likert+  |   .3605658   .1631984     2.21   0.027     .0404484    .6806833
                                QVSR  |   .6530014    .217334     3.00   0.003     .2266958    1.079307
                                      |
                                block |
                                1120  |  -.0394613   .3999922    -0.10   0.921     -.824055    .7451325
                                1130  |   .1122229   .4888311     0.23   0.818    -.8466304    1.071076
                                1210  |   .2603934   .3573776     0.73   0.466    -.4406108    .9613977
                                1221  |   .1590405   .3870899     0.41   0.681    -.6002452    .9183262
                                1222  |   .1167706   .3589129     0.33   0.745    -.5872453    .8207865
                                1223  |   .3752736   .3542866     1.06   0.290    -.3196675    1.070215
                                1231  |    .590805   .5119242     1.15   0.249    -.4133461    1.594956
                                1232  |   .1844716   .4214531     0.44   0.662    -.6422183    1.011162
                                1233  |   .4146649   .3641234     1.14   0.255    -.2995715    1.128901
                                1311  |   .5141573   .4362992     1.18   0.239    -.3416536    1.369968
                                1312  |   .5164363   .3896053     1.33   0.185    -.2477834    1.280656
                                1313  |   .3769042   .3597909     1.05   0.295    -.3288338    1.082642
                                1321  |   .5227243   .3304035     1.58   0.114    -.1253697    1.170818
                                1322  |   .2795255   .3398095     0.82   0.411    -.3870186    .9460696
                                1323  |    .416637   .3376886     1.23   0.217    -.2457469    1.079021
                                1331  |   .4599422   .3837642     1.20   0.231      -.29282    1.212704
                                1332  |   .1960915   .3840627     0.51   0.610    -.5572563    .9494393
                                1333  |   .4962335    .379317     1.31   0.191    -.2478054    1.240272
                                2010  |   .6149219   .4718874     1.30   0.193     -.310696     1.54054
                                2020  |   .5770042   .5409451     1.07   0.286     -.484072     1.63808
                                2030  |   .0686286    .414461     0.17   0.869    -.7443462    .8816034
                                3115  |   .6250333   .3424638     1.83   0.068    -.0467173    1.296784
                                3116  |   .5000896   .3393832     1.47   0.141    -.1656182    1.165797
                                3117  |   .3211441   .3300692     0.97   0.331    -.3262942    .9685824
                                3120  |   .3750294   .4456037     0.84   0.400    -.4990324    1.249091
                                3135  |  -.0141487    .404595    -0.03   0.972     -.807771    .7794736
                                3136  |   .4552114   .4205997     1.08   0.279    -.3698046    1.280227
                                3137  |  -.0490577   .3814782    -0.13   0.898    -.7973359    .6992205
                                3215  |   .2958093    .343618     0.86   0.389    -.3782053    .9698239
                                3216  |   .4621886   .3521129     1.31   0.190     -.228489    1.152866
                                3217  |   .2138551   .3473056     0.62   0.538    -.4673928    .8951029
                                3220  |  -.0834349   .3893766    -0.21   0.830     -.847206    .6803361
                                3235  |   .1008648   .3558703     0.28   0.777    -.5971828    .7989125
                                3236  |   .2069867   .3964076     0.52   0.602    -.5705758    .9845492
                                3237  |   .2834078   .4574377     0.62   0.536    -.6138668    1.180682
                                3315  |   .1074453    .400147     0.27   0.788    -.6774522    .8923428
                                3316  |   .3459978   .4363241     0.79   0.428    -.5098619    1.201857
                                3317  |  -.1922795   .4206439    -0.46   0.648    -1.017382    .6328231
                                3320  |   .1761001   .4457963     0.40   0.693    -.6983396     1.05054
                                3330  |   .4691635   .4153612     1.13   0.259     -.345577    1.283904
                                      |
                                _cons |  -.6057633   .3391609    -1.79   0.074    -1.271035    .0595086
-------------------------------------------------------------------------------------------------------

. lincom c.abs_votes_abortion_inw1LPP3N + 1.method#c.abs_votes_abortion_inw1LPP3N 

 ( 1)  abs_votes_abortion_inw1LPP3N + 1b.method#co.abs_votes_abortion_inw1LPP3N = 0

------------------------------------------------------------------------------
writing~nNST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .3837219   .1162126     3.30   0.001     .1557683    .6116756
------------------------------------------------------------------------------

. matrix EV_fig3[4,1] = r(estimate)

. matrix EV_fig3[4,2] = r(se)

. lincom c.abs_votes_abortion_inw1LPP3N + 2.method#c.abs_votes_abortion_inw1LPP3N 

 ( 1)  abs_votes_abortion_inw1LPP3N + 2.method#c.abs_votes_abortion_inw1LPP3N = 0

------------------------------------------------------------------------------
writing~nNST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .7442877   .1178942     6.31   0.000     .5130357    .9755398
------------------------------------------------------------------------------

. matrix EV_fig3[4,3] = r(estimate)

. matrix EV_fig3[4,4] = r(se)

. lincom c.abs_votes_abortion_inw1LPP3N + 3.method#c.abs_votes_abortion_inw1LPP3N 

 ( 1)  abs_votes_abortion_inw1LPP3N + 3.method#c.abs_votes_abortion_inw1LPP3N = 0

------------------------------------------------------------------------------
writing~nNST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   1.036723   .1867561     5.55   0.000      .670397     1.40305
------------------------------------------------------------------------------

. matrix EV_fig3[4,5] = r(estimate)

. matrix EV_fig3[4,6] = r(se)

. 
. 
. regress punish_FaST c.diffLPP3N##i.method  i.block

      Source |       SS           df       MS      Number of obs   =     1,542
-------------+----------------------------------   F(45, 1496)     =      1.34
       Model |  59.8682549        45  1.33040567   Prob > F        =    0.0668
    Residual |  1484.73865     1,496  .992472359   R-squared       =    0.0388
-------------+----------------------------------   Adj R-squared   =    0.0098
       Total |   1544.6069     1,541  1.00234063   Root MSE        =    .99623

------------------------------------------------------------------------------------
       punish_FaST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
         diffLPP3N |   .2536402   .2361063     1.07   0.283    -.2094943    .7167748
                   |
            method |
          Likert+  |  -.1763746   .2003305    -0.88   0.379    -.5693331    .2165838
             QVSR  |  -.1999328   .1998987    -1.00   0.317    -.5920442    .1921787
                   |
method#c.diffLPP3N |
          Likert+  |   .2935067   .3430128     0.86   0.392    -.3793305    .9663438
             QVSR  |   .4789939   .3459769     1.38   0.166    -.1996575    1.157645
                   |
             block |
             1120  |  -.3310659   .4110756    -0.81   0.421    -1.137412    .4752799
             1130  |  -.1477843    .502927    -0.29   0.769    -1.134301    .8387327
             1210  |  -.0949166   .3663452    -0.26   0.796    -.8135213    .6236881
             1221  |   -.395439   .4002302    -0.99   0.323    -1.180511    .3896328
             1222  |   .0588306    .371182     0.16   0.874    -.6692618     .786923
             1223  |   .2651306   .3628102     0.73   0.465    -.4465401    .9768014
             1231  |    .444459   .5262596     0.84   0.398    -.5878261    1.476744
             1232  |  -.1137695   .4329223    -0.26   0.793    -.9629686    .7354296
             1233  |  -.1714469   .3739315    -0.46   0.647    -.9049326    .5620388
             1311  |   -.311601   .4483194    -0.70   0.487    -1.191002    .5678003
             1312  |  -.3167187    .400373    -0.79   0.429    -1.102071    .4686334
             1313  |  -.2709482   .3696219    -0.73   0.464    -.9959804     .454084
             1321  |  -.0086417   .3398048    -0.03   0.980    -.6751863    .6579028
             1322  |   .0122505   .3490151     0.04   0.972    -.6723603    .6968614
             1323  |   .2081515   .3473848     0.60   0.549    -.4732614    .8895645
             1331  |  -.1770432   .3970649    -0.45   0.656    -.9559062    .6018199
             1332  |  -.1806845   .4005124    -0.45   0.652    -.9663101     .604941
             1333  |  -.2067935    .389648    -0.53   0.596    -.9711079    .5575209
             2010  |  -.4178771    .484671    -0.86   0.389    -1.368584    .5328298
             2020  |   .6906075   .5565448     1.24   0.215    -.4010835    1.782299
             2030  |  -.0278757   .4257515    -0.07   0.948    -.8630089    .8072576
             3115  |   .2455593   .3515372     0.70   0.485    -.4439987    .9351174
             3116  |   .0234181   .3490133     0.07   0.947    -.6611892    .7080255
             3117  |  -.0349798   .3392387    -0.10   0.918    -.7004138    .6304541
             3120  |  -.2956747   .4492767    -0.66   0.511    -1.176954    .5856044
             3135  |  -.0710223   .4158103    -0.17   0.864    -.8866554    .7446108
             3136  |   .0162756   .4397711     0.04   0.970    -.8463578    .8789091
             3137  |   .0526642   .3922159     0.13   0.893    -.7166873    .8220157
             3215  |   .2448557   .3537594     0.69   0.489    -.4490613    .9387728
             3216  |  -.1668231   .3621486    -0.46   0.645     -.877196    .5435498
             3217  |   .1518514   .3589854     0.42   0.672    -.5523169    .8560196
             3220  |  -.0043296   .4041908    -0.01   0.991    -.7971705    .7885112
             3235  |   .0143916    .366056     0.04   0.969    -.7036459    .7324291
             3236  |  -.1469779   .4069835    -0.36   0.718    -.9452967     .651341
             3237  |  -.3784913   .4703257    -0.80   0.421    -1.301059    .5440765
             3315  |    .279878   .4072554     0.69   0.492    -.5189743     1.07873
             3316  |   .2401028   .4480206     0.54   0.592    -.6387125    1.118918
             3317  |  -.1247793   .4327177    -0.29   0.773    -.9735771    .7240184
             3320  |  -.1288703   .4480445    -0.29   0.774    -1.007732    .7499918
             3330  |   .3805917   .4396367     0.87   0.387    -.4817781    1.242962
                   |
             _cons |   -.158663   .3588455    -0.44   0.658    -.8625568    .5452309
------------------------------------------------------------------------------------

. lincom c.diffLPP3N + 1.method#c.diffLPP3N 

 ( 1)  diffLPP3N + 1b.method#co.diffLPP3N = 0

------------------------------------------------------------------------------
 punish_FaST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .2536402   .2361063     1.07   0.283    -.2094943    .7167748
------------------------------------------------------------------------------

. matrix EV_fig3[5,1] = r(estimate)

. matrix EV_fig3[5,2] = r(se)

. lincom c.diffLPP3N + 2.method#c.diffLPP3N 

 ( 1)  diffLPP3N + 2.method#c.diffLPP3N = 0

------------------------------------------------------------------------------
 punish_FaST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .5471469   .2572357     2.13   0.034     .0425659    1.051728
------------------------------------------------------------------------------

. matrix EV_fig3[5,3] = r(estimate)

. matrix EV_fig3[5,4] = r(se)

. lincom c.diffLPP3N + 3.method#c.diffLPP3N 

 ( 1)  diffLPP3N + 3.method#c.diffLPP3N = 0

------------------------------------------------------------------------------
 punish_FaST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .7326341   .2588086     2.83   0.005     .2249679      1.2403
------------------------------------------------------------------------------

. matrix EV_fig3[5,5] = r(estimate)

. matrix EV_fig3[5,6] = r(se)

. 
. 
. regress proportionST c.diffLPP3N##i.method i.block

      Source |       SS           df       MS      Number of obs   =     1,521
-------------+----------------------------------   F(45, 1475)     =      1.97
       Model |  86.2915936        45  1.91759097   Prob > F        =    0.0002
    Residual |  1436.32402     1,475  .973778998   R-squared       =    0.0567
-------------+----------------------------------   Adj R-squared   =    0.0279
       Total |  1522.61562     1,520   1.0017208   Root MSE        =     .9868

------------------------------------------------------------------------------------
      proportionST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------------+----------------------------------------------------------------
         diffLPP3N |   .4737162   .2347876     2.02   0.044      .013163    .9342694
                   |
            method |
          Likert+  |  -.2144004   .1996092    -1.07   0.283    -.6059485    .1771477
             QVSR  |  -.3846788   .2000536    -1.92   0.055    -.7770987    .0077411
                   |
method#c.diffLPP3N |
          Likert+  |   .3384122   .3416164     0.99   0.322    -.3316935    1.008518
             QVSR  |   .9229285   .3459192     2.67   0.008     .2443825    1.601474
                   |
             block |
             1120  |  -.4248264   .4277862    -0.99   0.321     -1.26396    .4143077
             1130  |  -.6414147   .5117869    -1.25   0.210    -1.645322     .362493
             1210  |  -.2329446   .3816317    -0.61   0.542    -.9815433     .515654
             1221  |  -.7774368   .4132751    -1.88   0.060    -1.588106    .0332328
             1222  |  -.3241998   .3858438    -0.84   0.401    -1.081061    .4326613
             1223  |  -.1741882   .3781795    -0.46   0.645    -.9160152    .5676388
             1231  |   .3274323   .5348618     0.61   0.541    -.7217386    1.376603
             1232  |  -.3531328   .4445017    -0.79   0.427    -1.225056      .51879
             1233  |  -.5570318   .3885145    -1.43   0.152    -1.319132     .205068
             1311  |  -.6007964   .4592061    -1.31   0.191    -1.501563    .2999702
             1312  |  -.6067617   .4167573    -1.46   0.146    -1.424262    .2107383
             1313  |  -.6145623   .3846542    -1.60   0.110     -1.36909    .1399652
             1321  |  -.3931134   .3564842    -1.10   0.270    -1.092383    .3061565
             1322  |  -.2970405   .3650759    -0.81   0.416    -1.013164    .4190828
             1323  |   -.242392   .3639173    -0.67   0.505    -.9562426    .4714585
             1331  |     -.5807   .4103776    -1.42   0.157    -1.385686    .2242858
             1332  |  -.6251471   .4138716    -1.51   0.131    -1.436987    .1866926
             1333  |  -.3882454   .4031719    -0.96   0.336    -1.179097    .4026058
             2010  |  -.2470078   .5124864    -0.48   0.630    -1.252288     .758272
             2020  |  -.0597069    .563671    -0.11   0.916    -1.165389    1.045975
             2030  |  -.2652684   .4377343    -0.61   0.545    -1.123916    .5933797
             3115  |  -.0131723   .3681725    -0.04   0.971    -.7353697     .709025
             3116  |  -.2051365   .3655646    -0.56   0.575    -.9222185    .5119455
             3117  |  -.2208954   .3562818    -0.62   0.535    -.9197685    .4779776
             3120  |  -.5671415   .4608721    -1.23   0.219    -1.471176    .3368932
             3135  |   -.483202   .4283663    -1.13   0.259    -1.323474      .35707
             3136  |   -.348919   .4510459    -0.77   0.439    -1.233679    .5358406
             3137  |   .0085402   .4110444     0.02   0.983    -.7977535     .814834
             3215  |  -.0551891    .369783    -0.15   0.881    -.7805456    .6701673
             3216  |  -.3817873   .3781016    -1.01   0.313    -1.123461    .3598867
             3217  |  -.0608592   .3760499    -0.16   0.871    -.7985088    .6767904
             3220  |  -.4558929   .4171057    -1.09   0.275    -1.274076    .3622906
             3235  |  -.2708969   .3810806    -0.71   0.477    -1.018415    .4766207
             3236  |  -.5011749   .4198825    -1.19   0.233    -1.324805    .3224556
             3237  |  -.7760445   .4806132    -1.61   0.107    -1.718803    .1667136
             3315  |  -.0508606   .4204161    -0.12   0.904    -.8755378    .7738165
             3316  |  -.1006171   .4591636    -0.22   0.827      -1.0013    .8000661
             3317  |  -.2229939   .4446855    -0.50   0.616    -1.095277    .6492895
             3320  |  -.2287176   .4585988    -0.50   0.618    -1.128293    .6708577
             3330  |   .0717336   .4509493     0.16   0.874    -.8128366    .9563038
                   |
             _cons |  -.0000165   .3744815    -0.00   1.000    -.7345896    .7345566
------------------------------------------------------------------------------------

. lincom c.diffLPP3N + 1.method#c.diffLPP3N 

 ( 1)  diffLPP3N + 1b.method#co.diffLPP3N = 0

------------------------------------------------------------------------------
proportionST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .4737162   .2347876     2.02   0.044      .013163    .9342694
------------------------------------------------------------------------------

. matrix EV_fig3[6,1] = r(estimate)

. matrix EV_fig3[6,2] = r(se)

. lincom c.diffLPP3N + 2.method#c.diffLPP3N 

 ( 1)  diffLPP3N + 2.method#c.diffLPP3N = 0

------------------------------------------------------------------------------
proportionST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   .8121284   .2566316     3.16   0.002     .3087267     1.31553
------------------------------------------------------------------------------

. matrix EV_fig3[6,3] = r(estimate)

. matrix EV_fig3[6,4] = r(se)

. lincom c.diffLPP3N + 3.method#c.diffLPP3N 

 ( 1)  diffLPP3N + 3.method#c.diffLPP3N = 0

------------------------------------------------------------------------------
proportionST | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
         (1) |   1.396645   .2600475     5.37   0.000     .8865424    1.906747
------------------------------------------------------------------------------

. matrix EV_fig3[6,5] = r(estimate)

. matrix EV_fig3[6,6] = r(se)

. 
. 
. 
. putexcel set  "$pathtemp/EV_fig3", replace
note: file will be replaced when the first putexcel command is issued.

. putexcel A1=matrix(EV_fig3) 
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/EV_fig3.xlsx saved

. 
. 
. preserve

. 
. clear all

. 
. cd "$pathtemp"
/Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp

. import excel EV_fig3
(6 vars, 6 obs)

. 
. gen topic = _n

. 
. 
. rename A est1

. rename B se1

. rename C est2

. rename D se2

. rename E est3

. rename F se3

. 
. reshape long est se, i(topic) j(method)    
(j = 1 2 3)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations                6   ->   18          
Number of variables                   7   ->   4           
j variable (3 values)                     ->   method
xij variables:
                         est1 est2 est3   ->   est
                            se1 se2 se3   ->   se
-----------------------------------------------------------------------------

. 
. sort topic method

. gen order = _n

. gen lb = est - 1.96*se

. gen ub = est + 1.96*se

. 
. 
. tw (scatter est order,  legend(off) ylabel(0(0.2)2.2) yline(0, lc(black) lstyle(gs15)) ///
> text(2.2 1.5 "Gun", place(e)) ///
> text(2.2 3.9 "Immigration", place(e)) ///
> text(2.2 7.2 "Minimum", place(e)) ///
> text(2.0 7.4 "Wage", place(e)) ///
> text(2.2 10 "Abortion", place(e)) ///
> text(2.2 12.5 "DG punish (1)", place(e)) ///
> text(2.2 15.8 "DG punish (2)", place(e)) ///
> xlabel(1 "Likert" 2 "Likert +" 3 "QVSR" 4 " " 5 " " 6 " " 7 "Likert" 8 "Likert +" 9 "QVSR" ///
> 10 " " 11 " " 12 " " 13 "Likert" 14 "Likert +" 15 "QVSR" 16 " " 17 " " 18 " " , angle(45)labsize(small) ) ///
> xtitle(" ", size(zero))) ///
> (rcap lb ub order, xline(3.5) xline(6.5) xline(9.5) xline(12.5) xline(15.5))
(note:  named style gs15 not found in class linestyle, default attributes used)

. 
. 
. cd "$pathfig"
/Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/fig

. graph export "Fig3.pdf", replace 
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/fig/Fig3.pdf saved as PDF
    format

. 
. 
. restore

. 
. 
. erase "$pathtemp/EV_fig3.xlsx"

. 
. 
. 
. 
. *----- 
. *-------------------------------
. *---  Figure 4 -- 
. 
. 
. *-- recode and rename to help with coding 
. 
. recode sex (1 = 0) (2 =1), gen(Gender)
(3,940 differences between sex and Gender)

. 
. egen mean_GenderL = mean(Gender) if method == 1 , by(votes_genderw1LPP3N)
(2,608 missing values generated)

. egen mean_GenderLp = mean(Gender) if method == 2 , by(votes_genderw1LPP3N)
(2,614 missing values generated)

. egen mean_GenderQV = mean(Gender) if method == 3 , by(votes_genderw1LPP3N)
(2,706 missing values generated)

. 
. 
. egen count_Gender = count(votes_genderw1LPP3N), by(method votes_genderw1LPP3N)

. 
. 
. cd "$pathtemp"
/Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp

. 
. tw (lfitci Gender votes_genderw1LPP3N if method == 1,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_GenderL votes_genderw1LPP3N if method == 1 [w=count_Gender],  mc(black)  msymbol(oh) ///
> ylabel(-0.2(0.2)1, angle(horizontal) labsize(medsmall)) yline(0.50) xlabel(0(0.1)1, angle(horizontal)labsize(medsm
> all)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("Likert")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "Gender_fig4L.gph", replace 
(file Gender_fig4L.gph not found)
file Gender_fig4L.gph saved

. 
. 
. tw (lfitci Gender votes_genderw1LPP3N if method == 2,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_GenderLp votes_genderw1LPP3N if method == 2 [w=count_Gender],  mc(black)  msymbol(oh) ///
> ylabel(-0.2(0.2)1 , angle(horizontal) labsize(medsmall)) yline(0.50) xlabel(0(0.1)1, angle(horizontal)labsize(meds
> mall)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("Likert +")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "Gender_fig4Lpp3.gph", replace 
(file Gender_fig4Lpp3.gph not found)
file Gender_fig4Lpp3.gph saved

. 
. 
. tw (lfitci Gender votes_genderw1LPP3N if method == 3,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_GenderQV votes_genderw1LPP3N if method == 3 [w=count_Gender],  mc(black)  msymbol(oh) ///
> ylabel(-0.2(0.2)1, angle(horizontal) labsize(medsmall)) yline(0.50) xlabel(0(0.1)1, angle(horizontal)labsize(medsm
> all)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("QVSR")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "Gender_fig4QV.gph", replace 
(file Gender_fig4QV.gph not found)
file Gender_fig4QV.gph saved

. 
. 
. *** quadratic 
. 
. 
. tw (qfitci Gender votes_genderw1LPP3N if method == 1,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_GenderL votes_genderw1LPP3N if method == 1 [w=count_Gender],  mc(black)  msymbol(oh) ///
> ylabel(-0.2(0.2)1 , angle(horizontal) labsize(medsmall)) yline(0.50) xlabel(0(0.1)1, angle(horizontal)labsize(meds
> mall)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("Likert")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "Gender_fig4L_qua.gph", replace 
(file Gender_fig4L_qua.gph not found)
file Gender_fig4L_qua.gph saved

. 
. 
. tw (qfitci Gender votes_genderw1LPP3N if method == 2,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_GenderLp votes_genderw1LPP3N if method == 2 [w=count_Gender],  mc(black)  msymbol(oh) ///
> ylabel(-0.2(0.2)1 , angle(horizontal) labsize(medsmall)) yline(0.50) xlabel(0(0.1)1, angle(horizontal)labsize(meds
> mall)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("Likert +")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "Gender_fig4Lpp3_qua.gph", replace 
(file Gender_fig4Lpp3_qua.gph not found)
file Gender_fig4Lpp3_qua.gph saved

. 
. 
. tw (qfitci Gender votes_genderw1LPP3N if method == 3,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_GenderQV votes_genderw1LPP3N if method == 3 [w=count_Gender],  mc(black)  msymbol(oh) ///
> ylabel(-0.2(0.2)1, angle(horizontal)labsize(medsmall)) yline(0.50) xlabel(0(0.1)1, angle(horizontal)labsize(medsma
> ll)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("QVSR")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "Gender_fig4QV_qua.gph", replace 
(file Gender_fig4QV_qua.gph not found)
file Gender_fig4QV_qua.gph saved

. 
. graph combine  "Gender_fig4Lpp3.gph"  "Gender_fig4L.gph" "Gender_fig4QV.gph" ///
>  "Gender_fig4Lpp3_qua.gph"  "Gender_fig4L_qua.gph" "Gender_fig4QV_qua.gph", col(3)

. cd "$pathfig"
/Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/fig

. graph export "Fig4.pdf", replace 
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/fig/Fig4.pdf saved as PDF
    format

. 
. 
. erase "$pathtemp/Gender_fig4Lpp3.gph"  

. erase "$pathtemp/Gender_fig4L.gph" 

. erase "$pathtemp/Gender_fig4QV.gph" 

. erase "$pathtemp/Gender_fig4Lpp3_qua.gph"  

. erase "$pathtemp/Gender_fig4L_qua.gph" 

. erase "$pathtemp/Gender_fig4QV_qua.gph"

. 
. 
. 
. *----- 
. *-------------------------------
. *---  Figure 5 -- 
. 
. 
. 
. 
. egen mean_paidLL = mean(child2) if method == 1 , by(votes_paidLw1LPP3N)
(2,608 missing values generated)

. egen mean_paidLLp = mean(child2) if method == 2 , by(votes_paidLw1LPP3N)
(2,614 missing values generated)

. egen mean_paidLQV = mean(child2) if method == 3 , by(votes_paidLw1LPP3N)
(2,706 missing values generated)

. 
. egen count_paidL = count(votes_paidLw1LPP3N), by(method votes_paidLw1LPP3N)

. 
. cd "$pathtemp"
/Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp

. 
. tw (lfitci child2 votes_paidLw1LPP3N if method == 1,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_paidLL votes_paidLw1LPP3N if method == 1 [w=count_paidL],  mc(black)  msymbol(oh) ///
> ylabel(0.8(0.4)2.8, angle(horizontal) labsize(medsmall) ) yline(1.56) xlabel(0(0.1)1, angle(horizontal)labsize(med
> small)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("Likert", size(med))  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)
(note:  named style med not found in class gsize, default attributes used)

. graph save "paidL_fig5L.gph", replace 
(file paidL_fig5L.gph not found)
file paidL_fig5L.gph saved

. 
. 
. tw (lfitci child2 votes_paidLw1LPP3N if method == 2,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_paidLLp votes_paidLw1LPP3N if method == 2 [w=count_paidL],  mc(black)  msymbol(oh) ///
> ylabel(0.8(0.4)2.8 , angle(horizontal)labsize(medsmall)) yline(1.56) xlabel(0(0.1)1, angle(horizontal)labsize(meds
> mall)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("Likert +", size(med))  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)
(note:  named style med not found in class gsize, default attributes used)

. graph save "paidL_fig5Lpp3.gph", replace 
(file paidL_fig5Lpp3.gph not found)
file paidL_fig5Lpp3.gph saved

. 
. 
. tw (lfitci child2 votes_paidLw1LPP3N if method == 3,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_paidLQV votes_paidLw1LPP3N if method == 3 [w=count_paidL],  mc(black)  msymbol(oh) ///
> ylabel(0.8(0.4)2.8, angle(horizontal) labsize(medsmall)) yline(1.56) xlabel(0(0.1)1, angle(horizontal)labsize(meds
> mall)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("QVSR", size(med))  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)
(note:  named style med not found in class gsize, default attributes used)

. graph save "paidL_fig5QV.gph", replace 
(file paidL_fig5QV.gph not found)
file paidL_fig5QV.gph saved

. 
. 
. *** quadratic 
. 
. 
. tw (qfitci child2 votes_paidLw1LPP3N if method == 1,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_paidLL votes_paidLw1LPP3N if method == 1 [w=count_paidL],  mc(black)  msymbol(oh) ///
> ylabel(0.8(0.4)2.8 , angle(horizontal) labsize(medsmall)) yline(1.56) xlabel(0(0.1)1, angle(horizontal)labsize(med
> small)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "paidL_fig5L_qua.gph", replace 
(file paidL_fig5L_qua.gph not found)
file paidL_fig5L_qua.gph saved

. 
. 
. tw (qfitci child2 votes_paidLw1LPP3N if method == 2,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_paidLLp votes_paidLw1LPP3N if method == 2 [w=count_paidL],  mc(black)  msymbol(oh) ///
> ylabel(0.8(0.4)2.8 , angle(horizontal) labsize(medsmall)) yline(1.56) xlabel(0(0.1)1, angle(horizontal)labsize(med
> small)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "paidL_fig5Lpp3_qua.gph", replace 
(file paidL_fig5Lpp3_qua.gph not found)
file paidL_fig5Lpp3_qua.gph saved

. 
. 
. tw (qfitci child2 votes_paidLw1LPP3N if method == 3,  level(95) clp(shortdash) clc(black) ) ///
> (scatter mean_paidLQV votes_paidLw1LPP3N if method == 3 [w=count_paidL],  mc(black)  msymbol(oh) ///
> ylabel(0.8(0.4)2.8, angle(horizontal) labsize(medsmall)) yline(1.56) xlabel(0(0.1)1, angle(horizontal)labsize(meds
> mall)) ///
> ytitle("", size(medsmall)) xtitle("", size(medsmall)) ///
> title("")  legend(off) )
(analytic weights assumed)
(analytic weights assumed)
(analytic weights assumed)

. graph save "paidL_fig5QV_qua.gph", replace 
(file paidL_fig5QV_qua.gph not found)
file paidL_fig5QV_qua.gph saved

. 
. 
. graph combine  "paidL_fig5Lpp3.gph"  "paidL_fig5L.gph" "paidL_fig5QV.gph" ///
>  "paidL_fig5Lpp3_qua.gph"  "paidL_fig5L_qua.gph" "paidL_fig5QV_qua.gph", col(3)
(note:  named style med not found in class gsize, default attributes used)
(note:  named style med not found in class gsize, default attributes used)
(note:  named style med not found in class gsize, default attributes used)

.  cd "$pathfig"
/Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/fig

. graph export "Fig5.pdf", replace 
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/fig/Fig5.pdf saved as PDF
    format

. 
. 
. erase "$pathtemp/paidL_fig5Lpp3.gph"  

. erase "$pathtemp/paidL_fig5L.gph" 

. erase "$pathtemp/paidL_fig5QV.gph" 

. erase "$pathtemp/paidL_fig5Lpp3_qua.gph"  

. erase "$pathtemp/paidL_fig5L_qua.gph" 

. erase "$pathtemp/paidL_fig5QV_qua.gph"

. 
. 
. 
. 
. 
. *----- 
. *-------------------------------
. *---  Table 2  -- 
. 
. 
. 
. matrix EV_tab2 = J(3,6,0)

. matrix colnames EV_tab2 = "QVSR vs Likert" "Likert+ vs Likert" "QVSR vs LIkert+" "QVSR vs Likert" "Likert+ vs Like
> rt" "QVSR vs LIkert+" 

. matrix rownames EV_tab2 = "N" ///
> "F test" ///
> "Prob > F "

. 
. 
. ***------sureg wave 1 
. 
. *--- Likert versus QVSR
. 
. 
. local var LPP3

. foreach var in `var' {
  2.         
.         
. preserve
  3. 
. drop if method == 2
  4. 
. recode method (1 = 0) (3 = 1)
  5. 
. qui sureg (don_C_gunST c.votes_gunw1`var'N##i.method i.block) ///
> (don_C_wall_inST c.votes_wall_inw1`var'N##i.method i.block), small dfk coeflegend 
  6. parmest, saving("$pathtemp/est_tab2_LQV_w1", replace)  stars(0.1 0.05 0.01)
  7. matrix EV_tab2[1,1] = e(N)
  8. 
. test _b[don_C_gunST:1.method#c.votes_gunw1`var'N] + _b[don_C_wall_inST:1.method#c.votes_wall_inw1`var'N] = 0
  9. matrix EV_tab2[2,1] = r(F)
 10. matrix EV_tab2[3,1] = r(p)
 11. 
. restore 
 12. 
. 
. *--- Likert versus Likert+
.         
.         
. preserve
 13. 
. drop if method == 3
 14. 
. recode method (1 = 0) (2 = 1)
 15. 
. qui  sureg (don_C_gunST c.votes_gunw1`var'N##i.method i.block) ///
> (don_C_wall_inST c.votes_wall_inw1`var'N##i.method i.block), small dfk coeflegend 
 16. parmest, saving("$pathtemp/est_tab2_LLp_w1", replace)  stars(0.1 0.05 0.01)
 17. matrix EV_tab2[1,2] = e(N)
 18. 
. 
. test _b[don_C_gunST:1.method#c.votes_gunw1`var'N] + _b[don_C_wall_inST:1.method#c.votes_wall_inw1`var'N] = 0
 19. matrix EV_tab2[2,2] = r(F)
 20. matrix EV_tab2[3,2] = r(p)
 21. 
. restore 
 22. 
. 
. *--- Libert+ versus QVSR
.         
.         
. preserve
 23. 
. drop if method == 1
 24. 
. recode method (2 = 0) (3 = 1)
 25. 
. qui  sureg (don_C_gunST c.votes_gunw1`var'N##i.method i.block) ///
> (don_C_wall_inST c.votes_wall_inw1`var'N##i.method i.block), small dfk coeflegend 
 26. parmest, saving("$pathtemp/est_tab2_LpQV_w1", replace)  stars(0.1 0.05 0.01)
 27. matrix EV_tab2[1,3] = e(N)
 28. 
. test _b[don_C_gunST:1.method#c.votes_gunw1`var'N] + _b[don_C_wall_inST:1.method#c.votes_wall_inw1`var'N] = 0
 29. matrix EV_tab2[2,3] = r(F)
 30. matrix EV_tab2[3,3] = r(p)
 31. 
. restore 
 32. 
. 
. ***----- sureg wave 2 
. *--- Likert versus QVSR
. 
. preserve
 33. 
. drop if method == 2
 34. 
. recode method (1 = 0) (3 = 1)
 35. 
. qui  sureg (writing_minWNST c.abs_votes_minWw1`var'N##i.method i.block) ///
> (writing_abortionNST c.abs_votes_abortion_inw1`var'N##i.method i.block) ///
> (punish_FaST c.diff`var'N##i.method i.block) ///
> (proportionST c.diff`var'N##i.method i.block), small dfk coeflegend 
 36. parmest, saving("$pathtemp/est_tab2_LQV_w2", replace)  stars(0.1 0.05 0.01)
 37. matrix EV_tab2[1,4] = e(N)
 38.  
. test _b[writing_minWNST:abs_votes_minWw1`var'N#1.method] + ///
> _b[writing_abortionNST:abs_votes_abortion_inw1`var'N#1.method] + ///
> _b[punish_FaST:diff`var'N#1.method] + ///
> _b[proportionST:diff`var'N#1.method] = 0
 39. matrix EV_tab2[2,4] = r(F)
 40. matrix EV_tab2[3,4] = r(p)
 41. 
. restore 
 42. 
. 
. *--- Likert versus Likert+
. 
. preserve
 43. 
. drop if method == 3
 44. 
. recode method (1 = 0) (2 = 1)
 45. 
. qui sureg (writing_minWNST c.abs_votes_minWw1`var'N##i.method i.block) ///
> (writing_abortionNST c.abs_votes_abortion_inw1`var'N##i.method i.block) ///
> (punish_FaST c.diff`var'N##i.method i.block) ///
> (proportionST c.diff`var'N##i.method i.block), small dfk coeflegend 
 46. parmest, saving("$pathtemp/est_tab2_LLp_w2", replace)  stars(0.1 0.05 0.01)
 47. matrix EV_tab2[1,5] = e(N)
 48.  
.  
. test _b[writing_minWNST:abs_votes_minWw1`var'N#1.method] + ///
> _b[writing_abortionNST:abs_votes_abortion_inw1`var'N#1.method] + ///
> _b[punish_FaST:diff`var'N#1.method] + ///
> _b[proportionST:diff`var'N#1.method] = 0
 49. matrix EV_tab2[2,5] = r(F)
 50. matrix EV_tab2[3,5] = r(p)
 51. 
. restore 
 52. 
. 
. *--- Libert+ versus QVSR
. 
. preserve
 53. 
. drop if method == 1
 54. 
. recode method (2 = 0) (3 = 1)
 55. 
. qui sureg (writing_minWNST c.abs_votes_minWw1`var'N##i.method i.block) ///
> (writing_abortionNST c.abs_votes_abortion_inw1`var'N##i.method i.block) ///
> (punish_FaST c.diff`var'N##i.method i.block)  ///
> (proportionST c.diff`var'N##i.method i.block), small dfk coeflegend 
 56. parmest, saving("$pathtemp/est_tab2_LpQV_w2", replace)  stars(0.1 0.05 0.01)
 57. matrix EV_tab2[1,6] = e(N)
 58. 
. test _b[writing_minWNST:abs_votes_minWw1`var'N#1.method] + ///
> _b[writing_abortionNST:abs_votes_abortion_inw1`var'N#1.method] + ///
> _b[punish_FaST:diff`var'N#1.method] + ///
> _b[proportionST:diff`var'N#1.method] = 0
 59. matrix EV_tab2[2,6] = r(F)
 60. matrix EV_tab2[3,6] = r(p)
 61. 
. restore 
 62. 
. }
(1,350 observations deleted)
(2,614 changes made to method)
(file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LQV_w1.dta
    not found)
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LQV_w1.dta
    saved

 ( 1)  [don_C_gunST]1.method#c.votes_gunw1LPP3N + [don_C_wall_inST]1.method#c.votes_wall_inw1LPP3N = 0

       F(  1,  4730) =   28.14
            Prob > F =    0.0000
(1,258 observations deleted)
(2,706 changes made to method)
(file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LLp_w1.dta
    not found)
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LLp_w1.dta
    saved

 ( 1)  [don_C_gunST]1.method#c.votes_gunw1LPP3N + [don_C_wall_inST]1.method#c.votes_wall_inw1LPP3N = 0

       F(  1,  4936) =    7.87
            Prob > F =    0.0050
(1,356 observations deleted)
(2,608 changes made to method)
(file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LpQV_w1.dta
    not found)
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LpQV_w1.dta
    saved

 ( 1)  [don_C_gunST]1.method#c.votes_gunw1LPP3N + [don_C_wall_inST]1.method#c.votes_wall_inw1LPP3N = 0

       F(  1,  4746) =    8.24
            Prob > F =    0.0041
(1,350 observations deleted)
(2,614 changes made to method)
(file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LQV_w2.dta
    not found)
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LQV_w2.dta
    saved

 ( 1)  [writing_minWNST]1.method#c.abs_votes_minWw1LPP3N +
       [writing_abortionNST]1.method#c.abs_votes_abortion_inw1LPP3N + [punish_FaST]1.method#c.diffLPP3N +
       [proportionST]1.method#c.diffLPP3N = 0

       F(  1,  3728) =    8.49
            Prob > F =    0.0036
(1,258 observations deleted)
(2,706 changes made to method)
(file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LLp_w2.dta
    not found)
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LLp_w2.dta
    saved

 ( 1)  [writing_minWNST]1.method#c.abs_votes_minWw1LPP3N +
       [writing_abortionNST]1.method#c.abs_votes_abortion_inw1LPP3N + [punish_FaST]1.method#c.diffLPP3N +
       [proportionST]1.method#c.diffLPP3N = 0

       F(  1,  3892) =    3.18
            Prob > F =    0.0748
(1,356 observations deleted)
(2,608 changes made to method)
(file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LpQV_w2.dta
    not found)
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LpQV_w2.dta
    saved

 ( 1)  [writing_minWNST]1.method#c.abs_votes_minWw1LPP3N +
       [writing_abortionNST]1.method#c.abs_votes_abortion_inw1LPP3N + [punish_FaST]1.method#c.diffLPP3N +
       [proportionST]1.method#c.diffLPP3N = 0

       F(  1,  3804) =    1.21
            Prob > F =    0.2707

. 
. 
. 
. use "$pathtemp/est_tab2_LQV_w1", clear

. gen col = "col1"

. keep if parm == "1.method#c.votes_gunw1LPP3N" | parm == "1.method#c.votes_wall_inw1LPP3N"
(92 observations deleted)

.         rename parm variable

.         rename stderr se

.         rename estimate b

. save "$pathtemp/est_tab2_LQV_w1", replace
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LQV_w1.dta
    saved

. 
. use "$pathtemp/est_tab2_LLp_w1", clear

. gen col = "col2"

. keep if parm == "1.method#c.votes_gunw1LPP3N" | parm == "1.method#c.votes_wall_inw1LPP3N"
(92 observations deleted)

.         rename parm variable

.         rename stderr se

.         rename estimate b

. save "$pathtemp/est_tab2_LLp_w1", replace
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LLp_w1.dta
    saved

. 
. use "$pathtemp/est_tab2_LpQV_w1", clear

. gen col = "col3"

. keep if parm == "1.method#c.votes_gunw1LPP3N" | parm == "1.method#c.votes_wall_inw1LPP3N"
(92 observations deleted)

.         rename parm variable

.         rename stderr se

.         rename estimate b

. save "$pathtemp/est_tab2_LpQV_w1", replace
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LpQV_w1.dta
    saved

. 
. 
. use "$pathtemp/est_tab2_LQV_w2", clear

. gen col = "col4"

. keep if parm == "1.method#c.abs_votes_minWw1LPP3N" | parm == "1.method#c.abs_votes_abortion_inw1LPP3N" ///
> | parm == "1.method#c.diffLPP3N" | parm == "1.method#c.diffLPP3N"
(184 observations deleted)

.         rename parm variable

.         rename stderr se

.         rename estimate b

. save "$pathtemp/est_tab2_LQV_w2", replace
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LQV_w2.dta
    saved

. 
. use "$pathtemp/est_tab2_LLp_w2", clear

. gen col = "col5"

. keep if parm == "1.method#c.abs_votes_minWw1LPP3N" | parm == "1.method#c.abs_votes_abortion_inw1LPP3N" ///
> | parm == "1.method#c.diffLPP3N" | parm == "1.method#c.diffLPP3N"
(184 observations deleted)

.         rename parm variable

.         rename stderr se

.         rename estimate b

. save "$pathtemp/est_tab2_LLp_w2", replace
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LLp_w2.dta
    saved

. 
. use "$pathtemp/est_tab2_LpQV_w2", clear

. gen col = "col6"

. keep if parm == "1.method#c.abs_votes_minWw1LPP3N" | parm == "1.method#c.abs_votes_abortion_inw1LPP3N" ///
> | parm == "1.method#c.diffLPP3N" | parm == "1.method#c.diffLPP3N"
(184 observations deleted)

.         rename parm variable

.         rename stderr se

.         rename estimate b

. save "$pathtemp/est_tab2_LpQV_w2", replace
file /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/temp/est_tab2_LpQV_w2.dta
    saved

. 
. 
. use "$pathtemp/est_tab2_LQV_w1", clear

. append using "$pathtemp/est_tab2_LLp_w1"

. append using "$pathtemp/est_tab2_LpQV_w1"

. append using "$pathtemp/est_tab2_LQV_w2"
(variable eq was str15, now str19 to accommodate using data's values)
(variable variable was str33, now str41 to accommodate using data's values)

. append using "$pathtemp/est_tab2_LLp_w2"

. append using "$pathtemp/est_tab2_LpQV_w2"

. 
. 
. 
. 
. 
. **************
. **************
. ** LATEX code for Table 2 is in "tab2_raw.tex", please check "tab" folder, tab2.tex
. **************
. **************
. 
. log close
      name:  <unnamed>
       log:  /Users/cavaille/Dropbox/CO.who_cares/2.Data and Analyses/7.Replication file PSRM/log_main.log
  log type:  text
 closed on:  10 Feb 2024, 12:03:41
--------------------------------------------------------------------------------------------------------------------
